Abstract
This project will develop and test an empirically based theory of transit-dependency using a predictive model of transit mode choice in the Philadelphia region. We will also examine station-level shifts in transit use in response to the Covid-19 outbreak in the Philadelphia region and how these correspond with the distribution of transit dependents throughout the region.
Transit dependents are sometimes crudely defined in opposition to choice riders who generally have access to a private car but choose transit, generally commuter rail or subway, instead of driving. However, lower-income riders who rely on buses to accomplish their day-to-day travel needs and are sometimes classified as transit dependents may be among the transit users who are closest to choosing between transit and an alternative mode, particularly private cars. Small increases in earnings or changes in transit service quality may therefore have the biggest influence for transit users who are sometimes viewed or described as captive. Understanding who is most likely to respond to shifts in service quality and where they live is an essential part of understanding how service improvements and deteriorations are likely to impact public transit ridership. Findings may also provide insight into factors that may have contributed to overall reductions in transit ridership over the past decade.
Examining the neighborhood factors associated with higher or lower declines in ridership since the Covid-19 outbreak will provide additional insights into where transit service is most critical and how well service-criticality overlaps with areas where residents are most and least likely to respond to changes in service quality more generally.
In addition to contributing to the general literature on the determinants of bus ridership and theories of transit dependency, the analysis may provide evidence on the types and locations of neighborhoods that are most likely to increase or decrease transit use in response to service changes from a planned bus network redesign.
Description
This research project will involve three primary tasks:
1. Literature review. First, we will summarize the last 20 years of empirical work on the determinants of transit ridership. In addition to the general summary, we will focus on (1) choice ridership and transit dependency, (2) poverty and race, (3) bus network redesign, and (4) differences between bus ridership and other transit modes.
2. Choice ridership. Second, we will develop a theoretical and empirical estimation of choice riders using the 2012 regional household travel survey. This will emphasize the types and geographies of traveler who are closest to choosing between driving a car and taking transit on a given trip. Although the literature tends to emphasize relatively well-off rail users, we hypothesize that travelers closest to the 50% probability of choosing a car over transit are likely to be low-income bus riders. After identifying choice -riders based on this probabilistic approach, we will plot the density of their home-locations and conduct a factor analysis to identify specific subgroups of choice riders.
3. Analysis of Covid-19 ridership losses. Second, we will summarize and develop predictive models of which bus lines and bus stations have lost the most and least ridership since the outbreak of Covid-19. Predictor variables will include service characteristics, demographics around station, and time of day. We will also look for exogenous predictors that might influence service characteristics but are otherwise unrelated to ridership. Analysis will emphasize where and when ridership losses have been most stark and which types of neighborhoods are likeliest to generate the highest ridership in a time of severely reduced overall travel.
Engagement partners
The Philadelphia Office of Transportation, Infrastructure, and Sustainability is providing support in developing our research questions and predictive models. To ensure regular communication and feedback, we will support an intern and research assistant who will work half-time out of the Philadelphia office and half-time out of Professor Guerra’s research lab. The student will likely help contribute to the city’s upcoming transit plan.
SEPTA officials will tentatively provide boarding data by station by time of day from Automated Passenger Counters and provide feedback on study findings and interpretation.
DVRPC will provide support for estimating likelihood of taking transit using their 2012 household travel survey. Likely support will include the provision of estimation travel time and travel cost skims for trips taken in the survey.
Timeline
Work assembling the partners and data began in Spring 2019. Full project completion will be accomplished by 6/30/22.
Strategic Description / RD&T
Deployment Plan
Expected Outcomes/Impacts
Expected Outputs
TRID
Individuals Involved
Email |
Name |
Affiliation |
Role |
Position |
erickg@upenn.edu |
Guerra, Erick |
University of Pennsylvania |
PI |
Faculty - Adjunct |
Budget
Amount of UTC Funds Awarded
$243500.00
Total Project Budget (from all funding sources)
$243500.00
Documents
Type |
Name |
Uploaded |
Data Management Plan |
data_management_plan.docx |
June 26, 2020, 9:54 a.m. |
Presentation |
Mobility21_Guerra2020v2.pptx |
July 6, 2020, 5:25 a.m. |
Presentation |
What the heck is a choice rider? |
March 25, 2021, 10:18 a.m. |
Presentation |
What the heck is a choice rider? |
March 25, 2021, 10:18 a.m. |
Progress Report |
340_Progress_Report_2021-03-31 |
March 25, 2021, 10:19 a.m. |
Presentation |
What the heck is a choice rider? |
Sept. 30, 2021, 2:12 p.m. |
Presentation |
What the heck is a choice rider? |
Sept. 30, 2021, 2:12 p.m. |
Progress Report |
340_Progress_Report_2021-09-30 |
Oct. 5, 2021, 9 a.m. |
Publication |
Impact of TNC on travel behavior and mode choice: a comparative analysis of Boston and Philadelphiaing Autonomous Racing Overtake Maneuvers with RRT |
Oct. 24, 2021, 8:27 p.m. |
Publication |
What the heck is a choice rider? A theoretical framework and empirical model |
March 1, 2022, 6:50 a.m. |
Progress Report |
340_Progress_Report_2022-03-30 |
March 1, 2022, 8:36 a.m. |
Publication |
Are location affordability and fair housing on a collision course? Race, transportation costs, and the siting of subsidized housing |
April 6, 2022, 4:45 a.m. |
Publication |
Do denser neighborhoods have safer streets? population density and traffic safety in the Philadelphia Region |
April 6, 2022, 4:45 a.m. |
Publication |
Transit user perceptions of driverless buses |
April 6, 2022, 4:46 a.m. |
Publication |
Does lacking a car put the brakes on activity participation? Private vehicle access and access to opportunities among low-income adults |
April 6, 2022, 4:47 a.m. |
Publication |
Bus rapid transit in Solo, Indonesia: Lessons from a low ridership system |
April 6, 2022, 4:47 a.m. |
Progress Report |
340_Progress_Report_2022-09-30 |
Sept. 19, 2022, 10:19 a.m. |
Progress Report |
340_Progress_Report_2023-03-31 |
March 3, 2023, 6:41 a.m. |
Final Report |
Final_Report_-_340.pdf |
July 12, 2023, 1:17 p.m. |
Match Sources
No match sources!
Partners
Name |
Type |
The Philadelphia Office of Transportation, Infrastructure, and Sustainability |
Deployment Partner Deployment Partner |
Delaware Valley Regional Planning Commission |
Deployment Partner Deployment Partner |
SEPTA |
Deployment Partner Deployment Partner |